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Volume 29 Issue 8
Jan.  2011
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Zhang Jin, Fang Yong . An Independent Component Analysis Algorithm Based on Block-wise Contourlet Transform[J]. Journal of Electronics & Information Technology, 2007, 29(8): 1813-1816. doi: 10.3724/SP.J.1146.2005.01518
Citation: Zhang Jin, Fang Yong . An Independent Component Analysis Algorithm Based on Block-wise Contourlet Transform[J]. Journal of Electronics & Information Technology, 2007, 29(8): 1813-1816. doi: 10.3724/SP.J.1146.2005.01518

An Independent Component Analysis Algorithm Based on Block-wise Contourlet Transform

doi: 10.3724/SP.J.1146.2005.01518
  • Received Date: 2005-11-23
  • Rev Recd Date: 2006-08-21
  • Publish Date: 2007-08-19
  • Based on the characteristics of good sparsity and capturing effectively the smooth contours in natural images for Contourlet transform, a new independent component analysis algorithm is proposed by using the block-wise Contourlet transform in this paper. Experimental results show that the proposed algorithm is able to achieve a better performance in image separation.
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  • Jutten C and Herault J. Blind separation of sources, part I: An adaptive algorithm based on neuromimetic architecture [J].Signal Processing.1991, 24(1):1-10[2]Bronstein A M and Bronstein M M, et al.. Blind separation of reflections using sparse ICA. 4th International Symposium on Independent Component Analysis and Blind Signal Separation, Nara, Japan, 2003, 4: 227-232.[3]Bronstein A M and Bronstein M M, et al.. Sparse ICA for blind separation of transmitted and reflected images[J].International Journal of Imaging Science and Technology.2005, 15(1):84-91[4]Do M N and Vetterli M. Contourlets: A new directional multiresolution image representation[J].Conference Record of the Thirty-Sixth Asilomar Conference on Signals, Systems and Computers . 3-6 Nov.2002, Vol. 1:497-501[5]Zibulevsky M and Pearlmutter B A. Blind source separation by sparse decomposition[J].Neural Comp.2001, 13(4):863-[6]Zibulevsky M, Kisilev P, Zeevi Y Y, and Pearlmutter B A. Blind source separation via multimode sparse representation. In NIPS-2001, Morgan Kaufmann, San Mateo, CA, 2001: 185-191.[7]Kisilev P, Zibulevsky M, Zeevi Y Y, and Pearlmutter B A. Multiresolution framework for blind source separation. CCIT Report#317, Technion Press, 2000.[8]Lennon M, Mercier G, Mouchot M C, and Hubert-Moy L. Spectral unmixing of hyperspectral images with the Independent Components Analysis and wavelet packets. IGARSS, Sydney, NSW. 9-13 July 2001, Vol. 6: 2896-2898.
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